Morningstar’s New Fund Taxonomy Reveals Cost Spectrum That Reshapes Active vs. Passive Debate
For decades, the investment industry has operated with a binary map: active funds on one side, passive index funds on the other. Morningstar’s latest research platform update shatters that simplicity, introducing a four-tier classification that exposes a continuum of cost, strategy, and performance outcomes most investors never see. The new framework—rolling out first in Morningstar Direct before reaching retail users—splits active funds into discretionary and systematic buckets, while dividing passive offerings between strategic-beta (smart beta) and traditional index-tracking vehicles. The early data, analyzed through September 30, 2026, confirms what fee-conscious investors have long suspected: cost is a spectrum, not a bright line, and where a fund sits on that spectrum largely dictates its odds of success.
The Four-Quadrant Framework Replacing the Active-Passive Binary
Morningstar’s legacy taxonomy labeled every non-index fund “active” and every index fund “index”—obscuring massive differences in process, cost structure, and risk profile. The new Active/Passive Strategy data point creates four distinct cohorts:
- Active-Discretionary: Traditional manager-driven stock picking (human judgment, qualitative research, concentrated bets)
- Active-Systematic: Rules-based, quantitative strategies that deviate from benchmarks but follow disciplined models
- Strategic Beta (Smart Beta): Index-tracking funds that weight by factors—value, momentum, quality, low volatility—rather than market-cap
- Index-Tracking Non-Strategic Beta: Pure cap-weighted or broad-market replication (S&P 500, total market, sector indexes)
Two additional “Other” categories exist but contain too few funds for meaningful analysis. This granularity matters because an active-systematic fund charging 0.15% has more in common with a strategic-beta ETF at 0.20% than with a discretionary active fund at 0.85%—yet the old labels lumped them at opposite poles.
Lesson 1: Cost Is a Spectrum, Not a Bright Line
The average expense ratios across U.S. equity categories reveal a stair-step decline from discretionary active to pure index tracking. On an equal-weighted basis, active-discretionary funds averaged 0.78%, while active-systematic funds averaged 0.42%—a 36-basis-point gap. Strategic-beta funds sat at 0.31%, and traditional index trackers at just 0.11%.
When weighted by assets—reflecting what investors actually pay—the divergence widens dramatically:
| Strategy Type | Equal-Weighted Avg. ER | Asset-Weighted Avg. ER |
|---|---|---|
| Active-Discretionary | 0.78% | 0.59% |
| Active-Systematic | 0.42% | 0.28% |
| Strategic Beta | 0.31% | 0.18% |
| Index-Tracking (Non-Strategic) | 0.11% | 0.05% |
Asset-weighted, the average traditional index fund costs roughly one-twelfth what the average discretionary active fund charges (0.05% vs. 0.59%). The gap narrows in value and growth categories because heavyweights like Vanguard Value Index and iShares Russell 1000 Growth are classified as strategic beta—pulling that cohort’s asset-weighted average below pure index trackers in those styles.
Lesson 2: Lower Costs, Better Odds of Beating the Benchmark
Morningstar measured success rates—the percentage of funds outperforming their style-specific index—over trailing one-, three-, five-, and ten-year periods ending September 2026. The pattern is unambiguous: each step down the cost ladder correlates with higher success rates.
“Cheaper groupings—starting with active-systematic—were likelier to outperform over most periods than the priciest, active-discretionary. That was even true of the staidest of the staid: index-tracking non-strategic beta, where funds succeeded more often against the benchmarks than the funds paid to do so.”
Over the decade ended September 2026, active-systematic funds posted the highest average excess return (though still slightly negative on an equal-weighted basis), while discretionary active funds lagged most. Index-tracking non-strategic-beta funds succeeded more frequently than active-discretionary funds—a counterintuitive result explained by index selection: an S&P 500 tracker (15.33% annualized) beat the Russell 1000 benchmark (15.05%) used for many large-blend funds, provided tracking error and fees were minimal.
Critical caveat: These figures exclude dead funds, introducing survivorship bias that inflates active-discretionary results most—precisely because active funds die at higher rates than index funds. Even with this bias, the cost-success relationship holds.
Lesson 3: Active Management Doesn’t Deliver Superior Risk Control
A core active-management pitch is downside protection—human managers can supposedly navigate drawdowns better than rigid indexes. The new data challenges that narrative across three risk dimensions:
- Tracking Error: Active-discretionary funds showed the highest deviation from benchmarks (as expected), followed by active-systematic and strategic beta (similar), with cap-weighted trackers tightest.
- Volatility (Standard Deviation): Both active flavors were slightly more volatile than index-tracking funds over the ten-year window.
- Maximum Drawdown: Index-tracking funds experienced shallower peak-to-trough declines on average than either active cohort.
The risk-adjusted return metric—Sortino ratio relative to style benchmarks (which penalizes only downside volatility)—tells the same story: the cheaper the grouping, the better its risk-adjusted outcome versus its benchmark, with traditional index trackers leading.
What This Means for Portfolio Construction
The four-quadrant map isn’t academic—it changes how advisors and allocators should search for funds:
Match the Tool to the Conviction
If you want broad diversification but reject pure cap-weighting, cheap active-systematic or strategic-beta funds occupy the middle ground—offering factor tilts or rules-based active bets at 0.15%-0.30% rather than 0.70%+. The binary active/passive filter would miss these entirely.
Start With Cost, Then Layer Strategy
The data reinforces Morningstar’s long-standing hierarchy: expense ratio is the single most reliable predictor of future relative performance. Before debating factor models or manager tenure, screen for the lowest-cost quintile within your desired strategy bucket.
Complexity Carries Hidden Costs
Active-discretionary funds embed agency risk—manager turnover, style drift, key-person dependency, incentive misalignment. These aren’t captured in expense ratios but demand ongoing due diligence. Simpler strategies (systematic active, strategic beta, pure index) reduce monitoring burden without necessarily sacrificing returns.
Where the Data Lives—and What’s Next
The new Active/Passive Strategy and Passive-Index Tracking data points are currently exclusive to Morningstar Direct, the firm’s institutional research platform. Retail Morningstar.com users don’t yet have access, though integration into fund screener tools and analyst reports is expected. For now, investors can approximate the framework by cross-referencing:
- Morningstar’s “Active/Passive” field (legacy binary)
- Strategic Beta tag (identifies smart-beta funds)
- Management type (team vs. individual, quantitative vs. fundamental)
- Prospectus benchmark (reveals index-tracking intent)
Morningstar analyst Dan Sotiroff published a complementary deep-dive on the methodology, and the firm has signaled ongoing refinement as factor-based and semi-transparent active ETFs proliferate.
Bottom Line: The Map Just Got Better
The active-versus-passive debate never lacked opinions—it lacked precision. Morningstar’s four-tier taxonomy replaces a blunt instrument with a scalpel, revealing that cost, not philosophy, is the primary fault line separating winners from losers. Discretionary active management sits at the expensive, high-risk, low-success end of the spectrum. Pure index tracking anchors the cheap, low-risk, high-success end. In between lie two rapidly growing categories—active-systematic and strategic beta—that offer nuanced trade-offs for investors who want more than cap-weighting but refuse to pay 70 basis points for it.
The lesson isn’t that active management fails. It’s that expensive active management fails—and the new data makes it impossible to hide that fact behind a binary label.
Finance, Business, Investing, Mutual Funds, ETFs, Morningstar, Active Management, Passive Investing, Strategic Beta, Smart Beta, Expense Ratios, Fund Classification, Portfolio Construction, Risk-Adjusted Returns, Asset Management, Financial Research, Investment Costs, Market Analysis, Personal Finance, Wealth Management
